1. Technical Field
The present invention relates to an information processing method for a body motion signal, an information processing system for a body motion signal, an information processing apparatus for a body motion signal, displaying apparatus, a displaying method, a recording medium on which a program is recorded, a program, a body motion signal detecting apparatus, a method of detecting a body motion signal, an outputting apparatus, an outputting method, a diagnosing method of diagnosing an illness, a diagnosing system for diagnosing an illness, and a diagnosing apparatus for diagnosing an illness which are preferably used in, for example, evaluation of the severity or state change of Parkinson's disease.
2. Background Art
In Japan, the prevalence rate of Parkinson's disease reaches 100 to 150 per 100,000. With respect to Parkinson's disease, it is impossible to observe a notable finding in diagnostic imaging of the brain. Therefore, the Yahr rating scale, the UPDRS, and the like are used for classification and evaluation of Parkinson's disease patients.
However, these methods involve subjective evaluations of the doctor, the patient, and the like, and hence it is sometimes difficult to perform quantitative and objective determination. Among symptoms of Parkinson's disease, tremor, akinesia, and rigidity are known as three main symptoms. All of these symptoms do not always appear during, for example, diagnosis by a doctor.
Furthermore, Parkinson's disease is characterized also by abnormality gait, and presents various symptoms such as a slow gait, a small-step gait, and the like depending on the severity or the time of a day.
Information related to such abnormality gait is empirically known only by a complaint of the patient and his/her family. As it now stands, therefore, it is very difficult for a medical specialist to diagnose Parkinson's disease and know the pathological condition, only by examinations in an outpatient visit and a round in the hospital.
In the past, therefore, a system for non-invasively measuring Parkinson's disease has been proposed. An apparatus which analyzes the gait rhythm of a subject to early detect a reduction of the neurological system function has been proposed by the present inventors (see JP-A-2000-166877).
According to the invention disclosed in JP-A-2000-166877, it is possible to determine whether the subject suffers from a neurological disease such as Parkinson's disease or not. However, it is difficult to finely evaluate the severity or change of the pathological condition.
In order to evaluate Parkinson's disease, the gait rhythm of a subject must be always correctly measured. However, the time period which is required for one step in human walking (the time period ranging from a landing of a same foot, e.g., the right foot to the next landing of the right foot, hereinafter referred to as the gait cycle) is not constant even in a healthy subject, and always fluctuates.
In order to, considering this fluctuation, correctly obtain the cycle of each step (one cycle), for example, the peak position must be correctly detected from a time-series signal of the absolute value of an acceleration signal. When an objective phenomenon or waveform is to be extracted from a noisy signal as described above, pattern matching such as autocorrelation or cross-correlation is conventionally often used.
Specifically, a method of detecting a peak corresponding to an R wave from a correlation value between an electrocardiogram waveform and template data is disclosed (see JP-A-2004-89314). However, a way how to determine an actual peak from the correlation value is not disclosed.
Moreover, a method of deciding a peak position from matching between a vertical component of an acceleration and a predetermined waveform has been disclosed (see JP-A-2007-244495). However, the disclosure is made in obscure description that a peak is set in the case where the degree of similarity is high, and the method is not described in detail.
Moreover, preconditions that band division of a signal is performed in the determination of a peak and the pass bandwidth in the vertical direction is set to 2 to 4 Hz, and that a threshold of an energy ratio is disposed are set. Therefore, the method cannot cope with the case where the way or cycle of walking is suddenly largely changed. Moreover, the gravitational component of an acceleration is used for determining the vertical direction, and hence the method cannot cope with a process of a signal from an acceleration sensor which does not measure the gravitational component.
Furthermore, a method which can accurately detect the gait rhythm has been proposed (see JP-A-2008-154733). However, the method has a limitation in that the electric field of the human body must be measured. Moreover, the duration and frequency band for detecting the gait must be set as preconditions.
Also a diagnosis apparatus for Parkinson's disease in which a signal obtained from an acceleration sensor is analyzed has been proposed (see JP-A-2009-291379). JP-A-2009-291379 discloses that feature points are extracted from the waveform of the rhythm, and the time interval between adjacent feature points is set as the cycle of the rhythm. However, a specific method of correctly extracting feature points is not clearly described.
In a measurement method for evaluation of Parkinson's disease, from a further practical view point, the position where a device is attached is not fixed, and the method is requested to cope with a situation where the position of the device is changed or shifted with the elapse of time. In such a case, a signal is susceptible to influence of noises. Also in the case where, due to an illness such as Parkinson's disease, the walk cannot be forcefully performed or is accompanied by shakes, the gait waveform is disturbed.
Moreover, there is a case where, due to an illness such as Parkinson's disease, the gait cycle is suddenly prolonged or shortened during gait. Such a case occurs when a patient runs down stairs. Usually, the gait cycle is about 1 sec., and sometimes suddenly shortened to 0.5 sec. or shorter or prolonged to 2 sec. or longer.
Also a Parkinson's disease patient sometimes shows freezing of gait in which the gait cycle is suddenly shortened. Accurate detection of freezing of gait is very important for knowing the pathological condition. In the case where the gait pace is rapidly changed, it is difficult for a spectrum analyzing method in which an average cycle of a signal is obtained, to distinguish whether the obtained cycle is caused by a gait of a cycle of 0.5 sec. or by the time interval of 0.5 sec. between the right and left feet in the normal gait of a cycle of 1 sec.
When preconditions that the gait cycle is in the vicinity of 1 sec. are set as conventionally performed in the above-described spectrum analyzing method, the method cannot cope with a gait which is largely deviated from the preconditions.
In addition to Parkinson's disease, furthermore, with respect to various illnesses or diseases which cause impairment in the nervous system, muscles, skeleton, and the like related to a gait, such as stroke, spinal cord injury, cerebral palsy, myelodysplasia, muscular dystrophy, osteoarthritis, rheumatoid arthritis, multiple sclerosis, alcoholic intoxication, dementia, and hydrocephalus, it is desired to adequately know the pathological condition based on the gait rhythm.